Seleção genômica para características longitudinais de bovinos da raça Holandesa

Características longitudinais são de grande importância para a produção animal, no entanto, quando se trata de seleção genômica vários métodos estão sendo avaliados para características pontuais, como produção de leite em idades específicas ou produção total. Dessa forma, a aplicação destes métodos a trajetórias completas do fenótipo de interesse ao longo do tempo pode ser uma ferramenta importante para a tomada de decisão do melhor momento para seleção dos animais. No presente estudo foram utilizados dados de produção de leite, porcentagem de gordura, porcentagem de proteína e escore de células somáticas de bovinos leiteiros da raça Holandesa em uma metodologia de dois estágios: i) os modelos não lineares de Wood (1967), Cobby & Le Du (1978) e Wilmink (1987) foram ajustados aos dados de cada característica; ii) as estimativas de parâmetros obtidas para as curvas individuais no modelo que proporcionou melhor ajuste aos dados (Wilmink) foram utilizadas como fenótipos nas análises genômicas. Além dos modelos não lineares, também foi utilizado um modelo de regressão aleatória (RRM), considerando polinômios de Legendre quadráticos para a modelagem dos efeitos genético aditivo e de ambiente permanente. No segundo estágio foram testados diferentes métodos para estimação dos valores genéticos genômicos (GEBV): RR-BLUP e LASSO, que consideraram como fenótipos as estimativas dos parâmetros obtidas anteriormente e os coeficientes de regressão estimados via RRM. A correspondência de fenótipos e GEBV foi verificada por meio de validação cruzada, utilizando o método k-fold. Para todas as características estudadas e todos os parâmetros estimados pelo modelo de Wilmink (1987), as acurácias da predição genômica foram baixas quando o RR-BLUP foi utilizado. Além disso, o parâmetro c apresentou acurácias próximas de zero para quase todas as características. As acurácias de predição obtidas para os coeficientes de regressão aleatória foram de magnitude moderada a alta (>0,67) demonstrando que o uso de coeficientes de regressão aleatória pode ser uma boa alternativa para predição genômica considerando dados longitudinais.Longitudinal traits are of great importance for animal production, however, when it comes to genomic selection several methods are being evaluated for specific traits, such as milk yield in specific ages or total yield. Thus, applying these methods to complete trajectories of the phenotype of interest over time can be an important tool for helping to decide the best time to select the animals. In this study, milk yield, fat and protein percentage, and somatic cell score data of dairy cattle were used, in a two-stage procedure: i) where the nonlinear Wood (1967), Cobby & Le Du (1978) and Wilmink (1987) were adjusted; ii) the model that provided the best fit was the Wilmink model (1987), whose parameter estimates were used as phenotypes later. In addition to the non-linear models, it was also used a random regression model, considering quadratic Legendre polynomials to model the additive genetic and permanent environment effects. In the second stage different methods for estimation of genomic breeding values (GEBV) were applied: RR-BLUP and LASSO, which considered as phenotypes the estimated parameters previously obtained and the random regression coefficients. The correspondence between phenotypes and GEBV was verified by through cross validation using the k-fold method. For all traits, the genomic prediction accuracies of Wilmink’s model parameters were low when RR-BLUP was used. Furthermore, the accuracies for parameter c showed values close to zero for most traits. The prediction accuracies for random regression coefficients were moderate to high, above 0.67, and demonstrated that the use of random regression coefficients can be a good alternative for genomic prediction using longitudinal data.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

Genetic and environmental effects on scores of conformation, precocity and muscling in long yearling Nellore cattle

Os escores visuais de conformação (C), precocidade (P) e musculosidade (M) são usados para acessar indiretamente características relacionadas à terminação e composição de carcaça. Neste estudo, objetivou-se analisar como a idade da vaca ao parto (AC), idade (YA) e peso do animal ao sobreano (YW) influenciam os escores de bovinos da raça Nelore, além de estimar suas herdabilidades. Foram estimadas funções de regressão dos efeitos de AC, YA e YW sobre os escores C, P e M, após a absorção do efeito de grupo de contemporâneos (CG). As herdabilidades foram estimadas por máxima verossimilhança restrita, considerando-se quatro diferentes modelos que incluíram o efeito genético aditivo de animal como aleatório, e diferentes covariáveis (AC, YA e YW) como efeitos fixos. Nas análises de regressão, as covariáveis, tanto linear como quadrática, influenciaram significativamente os escores C, P e M. Os coeficientes de determinação dos modelos para YA e AC foram de pequena magnitude, provavelmente devido à absorção do efeito de CG. As estimativas de herdabilidade para os escores variaram de 0,13 a 0,36 para C, de 0,32 a 0,36 para P, e de 0,35 a 0,38 para M, considerando todos os modelos utilizados, indicando que C, P e M respondem à seleção direta. A classificação dos animais de acordo com seus valores genéticos, principalmente em relação a C, variou de acordo com os efeitos de ambiente incluídos nos modelos.s.The visual scores for conformation (C), precocity (P) and muscle (M) are used to indirectly assess traits related to termination and carcass composition. This study analyzes how age of dam at calving (AC), long yearling age (YA) and long yearling weight (YW) of the animal affect the scores of Nellore cattle, and estimates their heritability. Regression functions were estimated to determine the AC, YA and YW effects on C, P and M scores after the contemporary group (CG) effect being absorbed. The heritabilities were estimated by restricted maximum likelihood using four different models that included animal additive genetic effect as random and different covariates (AC, YA and YW) as fixed effects. The regression analysis showed that the covariates, either linear or quadratic, significantly influenced the scores of C, P and M. The determination coefficients of the models for YA and AC were small, probably due to the CG bias removal. The heritability estimates for the scores ranged from 0.13 to 0.36 for C; 0.32 to 0.36 for P; and, 0.35 to 0.38 for M, for all models, indicating that C, P and M respond to direct selection. The classification of animals according to their breeding values, especially in relation to C, varied according to the environmental effects included in the models

Genetic parameters and association between longevity and milk production in buffaloes using the ssGBLUP method

ABSTRACT The objectives of this work were to estimate the genetic parameters for the traits longevity (LG) and accumulated milk yield at 305 days (MY305) using a bitrait animal model and the single-step GBLUP method and estimate the genetic gain for LG through direct and indirect selection for MY305. We used 4,057 records of first lactations of Murrah dairy buffaloes, collected between 1987 and 2020, belonging to six Brazilian herds located in the states Ceará, Rio Grande do Norte, and São Paulo and 960 animals genotyped using the 90K Axiom Buffalo Genotyping (Thermo Fisher Scientific, Santa Clara, CA) to estimate the genetic parameters. The heritability estimate was 0.25 for MY305 and 0.13 for LG. The genetic gain for LG was 0.13 months under direct selection, and 0.14 months under indirect selection, which results in a relative selection efficiency of 11% under selection for MY305 compared with the direct selection. The genetic correlation between the two traits was 0.77, indicating that animals with genetic potential for high MY305 tend to live longer. The genetic trends for MY305 and LG were 0.22 kg/year and 5.20 days/year, respectively, indicating a positive response, which reaffirms its relationship with the high genetic correlation between the two traits

Genetic parameters and association between longevity and milk production in buffaloes using the ssGBLUP method

The objectives of this work were to estimate the genetic parameters for the traits longevity (LG) and accumulated milk yield at 305 days (MY305) using a bitrait animal model and the single-step GBLUP method and estimate the genetic gain for LG through direct and indirect selection for MY305. We used 4,057 records of first lactations of Murrah dairy buffaloes, collected between 1987 and 2020, belonging to six Brazilian herds located in the states Ceará, Rio Grande do Norte, and São Paulo and 960 animals genotyped using the 90K Axiom Buffalo Genotyping (Thermo Fisher Scientific, Santa Clara, CA) to estimate the genetic parameters. The heritability estimate was 0.25 for MY305 and 0.13 for LG. The genetic gain for LG was 0.13 months under direct selection, and 0.14 months under indirect selection, which results in a relative selection efficiency of 11% under selection for MY305 compared with the direct selection. The genetic correlation between the two traits was 0.77, indicating that animals with genetic potential for high MY305 tend to live longer. The genetic trends for MY305 and LG were 0.22 kg/year and 5.20 days/year, respectively, indicating a positive response, which reaffirms its relationship with the high genetic correlation between the two trait

Genetic parameters and alternatives for evaluation and ranking of Nellore young bulls in pasture performance tests

The objective of this study was to estimate (co)variance components for weight at 550 days, average daily gain and an index with both traits, and to compare alternatives for evaluation and ranking of Nellore young bulls in pasture performance tests. The heritability estimates were 0.73, 0.31 and 0.44 for weight at 550 days, average daily gain and index, respectively. Animals were ranked according to their predicted breeding values or the phenotypic deviations in relation to the mean of the test. Although the correlations between breeding values and phenotypic deviations were high, there were differences in the number of animals selected in common when the selection criteria were the predicted breeding values or the phenotypic deviations. Mixed models are more appropriate than the least squares method and should be utilized in the evaluation of young bulls in performance tests

X chromosome variants are associated with male fertility traits in two bovine populations

BACKGROUND: Twenty-five phenotypes were measured as indicators of bull fertility (1099 Brahman and 1719 Tropical Composite bulls). Measurements included sperm morphology, scrotal circumference, and sperm chromatin phenotypes such as DNA fragmentation and protamine deficiency. We estimated the heritability of these phenotypes and carried out genome-wide association studies (GWAS) within breed, using the bovine high-density chip, to detect quantitative trait loci (QTL). RESULTS: Our analyses suggested that both sperm DNA fragmentation and sperm protamine deficiency are heritable (h2 from 0.10 to 0.22). To confirm these first estimates of heritability, further studies on sperm chromatin traits, with larger datasets are necessary. Our GWAS identified 12 QTL for bull fertility traits, based on at least five polymorphisms (P